Voice initiated purchase request

ABSTRACT

Methods are described herein related to enabling users to purchase a product or service by providing a voice request and/or an image. An example method may involve: (a) receiving, by a hybrid response system (“HRS”), a first speech-segment message that comprises a speech segment and is associated with a user-account, (b) the HRS determining that the speech segment indicates a purchase request, (c) the HRS determining a target product/service based on at least the purchase request, (d) the HRS determining a confidence level associated with a purchase of the target product/service, (e) if the confidence level is greater than or equal to a threshold level, then the HRS sending a purchase order, via the associated user-account, for the target product or service, otherwise, the HRS sending the purchase request and the target product/service to at least one guide computing system to facilitate a response to the purchase request.

BACKGROUND

Unless otherwise indicated herein, the materials described in thissection are not prior art to the claims in this application and are notadmitted to be prior art by inclusion in this section.

Computing devices such as personal computers, laptop computers, tabletcomputers, cellular phones, and countless types of Internet-capabledevices are increasingly prevalent in numerous aspects of modern life.Over time, the manner in which these devices are providing informationto users is becoming more intelligent, more efficient, more intuitive,and/or less obtrusive.

As computing devices become smaller and more portable, traditional inputdevices such as keyboards, mice, and even touchscreens, may not be asfeasible as they once were. As such, speech-based interfaces arebecoming an increasingly popular way of allowing users to interact withtheir computing devices. Speech-based interfaces may be particularlyuseful on devices such as head-mountable displays (HMDs) and mobilephones, where other types of user-input devices and/or other modalitiesof user input may be limited, or may not even be feasible.

SUMMARY

Example embodiments may relate to enabling users to purchase a productor service via a voice request that is sent to a hybrid human andcomputer-automated response system. More specifically, exampleembodiments may be implemented in the context of a hybrid responsesystem, which is configured to provide responses to voice requests thatare sent from a client device, such as a head-mountable device. Thehybrid response system may provide an automated identification of atarget product or service in response to the voice request.Alternatively, the hybrid response may determine that human assistanceis needed to complete a response to the voice request, in which case thevoice request may be sent to one or more guide computing devices thatfacilitate a human-assisted response. In either case, an image may alsobe provided to the hybrid response system, where the image may be of atleast a portion of the target product, an advertisement, a productlabel, product packaging, and/or a UPC bar code to facilitate a responseto the purchase request. Once a target product or service has beenidentified, a purchase order may be sent via the user-account associatedwith the voice request.

In one aspect, a method includes: (a) receiving, by a computing system,a first speech-segment message, wherein the first speech-segment messagecomprises a speech segment, and wherein the first speech-segment messageis associated with a user-account, (b) determining, by the computingsystem that the speech segment indicates a purchase request, (c)determining, by the computing system, a target product or service basedon at least the purchase request, (d) determining, at the computingsystem, a confidence level associated with a purchase of the targetproduct or service, (e) if the confidence level is greater than or equalto a threshold level, then the computing system sending a purchaseorder, via the associated user-account, for the target product orservice; and otherwise, if the confidence level is less than thethreshold level, then the computing system sending the purchase requestand the target product or service to at least one guide computing systemto facilitate a response to the purchase request by the at least oneguide computing system.

In another aspect, a method includes: (a) receiving, by a client device,a first speech segment, wherein the first speech segment comprises apurchase request, wherein the client device is associated with auser-account, (b) receiving an image, by a client device, wherein theimage comprises at least one target-product-or-service detail, (c)determining, by the client device, a target product or service based onat least the purchase request, (d) determining, by the client device, aconfidence level associated with a purchase of the target product orservice, and (e) if the confidence level is greater than or equal to athreshold level, then the client device sending a purchase order, viathe associated user-account, for the target product or service, andotherwise, if the confidence level is less than the threshold level,then (i) the client device sending a purchase-request message comprisingthe purchase request and the image, (ii) the client device receiving atarget-product-or-service identification message comprising a secondtarget product or service, and (iii) the client device sending apurchase order for the second target product or service.

In a further aspect, a non-transitory computer-readable medium isprovided. The non-transitory computer readable medium is configured tostore program instructions that, when executed by a processor, cause theprocessor to carry out functions comprising: (a) receiving, by acomputing system, a first speech-segment message, wherein the firstspeech-segment message comprises a speech segment, and wherein the firstspeech-segment message is associated with a user-account, (b)determining, by the computing system that the speech segment indicates apurchase request, (c) determining, by the computing system, a targetproduct or service based on at least the purchase request, (d)determining, at the computing system, a confidence level associated witha purchase of the target product or service, (e) if the confidence levelis greater than or equal to a threshold level, then the computing systemsending a purchase order, via the associated user-account, for thetarget product or service; and otherwise, if the confidence level isless than the threshold level, then the computing system sending thepurchase request and the target product or service to at least one guidecomputing system to facilitate a response to the purchase request by theat least one guide computing system.

Further example embodiments may include: (a) means for receiving, by acomputing system, a first speech-segment message, wherein the firstspeech-segment message comprises a speech segment, and wherein the firstspeech-segment message is associated with a user-account, (b) means fordetermining, by the computing system that the speech segment indicates apurchase request, (c) means for determining, by the computing system, atarget product or service based on at least the purchase request, (d)means for determining, at the computing system, a confidence levelassociated with a purchase of the target product or service, (e) if theconfidence level is greater than or equal to a threshold level, thenmeans for the computing system sending a purchase order, via theassociated user-account, for the target product or service; andotherwise, if the confidence level is less than the threshold level,then means for the computing system sending the purchase request and thetarget product or service to at least one guide computing system tofacilitate a response to the purchase request by the at least one guidecomputing system.

These as well as other aspects, advantages, and alternatives will becomeapparent to those of ordinary skill in the art by reading the followingdetailed description, with reference where appropriate to theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating components of a system, in whichan example embodiment may be implemented.

FIG. 2 is a block diagram showing functional components of a system,according to an example embodiment.

FIG. 3A illustrates a wearable computing system according to an exampleembodiment.

FIG. 3B illustrates an alternate view of the wearable computing deviceillustrated in FIG. 3A.

FIG. 3C illustrates another wearable computing system according to anexample embodiment.

FIG. 3D illustrates another wearable computing system according to anexample embodiment.

FIGS. 3E to 3G are simplified illustrations of the wearable computingsystem shown in FIG. 3D, being worn by a wearer.

FIG. 4 is a simplified block diagram of a computing device according toan example embodiment.

FIG. 5 is a flow chart illustrating a method, according to an exampleembodiment.

FIG. 6 is a flow chart illustrating a method, according to an exampleembodiment.

FIG. 7 is an illustration of screens from an HMD display, in accordancewith an illustrative application of an example embodiment.

DETAILED DESCRIPTION

Example methods and systems are described herein. It should beunderstood that the words “example,” “exemplary,” and “illustrative” areused herein to mean “serving as an example, instance, or illustration.”Any embodiment or feature described herein as being an “example,” being“exemplary,” or being “illustrative” is not necessarily to be construedas preferred or advantageous over other embodiments or features. Theexample embodiments described herein are not meant to be limiting. Itwill be readily understood that the aspects of the present disclosure,as generally described herein, and illustrated in the figures, can bearranged, substituted, combined, separated, and designed in a widevariety of different configurations, all of which are explicitlycontemplated herein.

I. OVERVIEW

Example methods may help to make the process of purchasing goods orservices easier for consumers via a hybrid response system that can usecomputer-automated purchasing processes and can enlist the help of ahuman guide where appropriate, in order to make purchases on behalf of aconsumer.

For example, a user may speak a command or request (i.e., a speechsegment) that is interpreted as being a purchase request or a “buy forme” request. The voice request may be spoken and detected by the user'scomputing device, such as by a head-mountable display (HMD). The voicerequest may then be analyzed to determine whether an automated responsesystem may accurately determine the product or service the user wouldlike to purchase. For instance, a confidence metric associated with aproduct or service may be determined by an automated response system. Ifthe confidence metric is above a given threshold, the purchase may beexecuted automatically on behalf of the user.

If a product or service cannot be automatically determined or if theresult is too uncertain, the voice request may be sent to a human guideto assist in carrying out the purchase. If the user has given permissionfor certain user information to be utilized by the hybrid responsesystem, the guide may be given access to particularized user informationto facilitate determining what product or service to buy. For instance,the user may provide preferred shipping methods, preferred retailers,cost versus quality preferences, color preferences, and so on. The guidemay also be given access to past purchases by the user, which may helpthe guide interpret the user's current request.

In situations in which the methods and systems discussed herein collectpersonal information about users, or may make use of personalinformation, the users may be provided with an opportunity to controlwhether programs or features collect user information (e.g., informationabout a user's social network, social actions or activities, profession,a user's preferences, or a user's current location), or to controlwhether and/or how to receive content from the content server that maybe more relevant to the user. In addition, certain data may be treatedin one or more ways before it is stored or used, so that personallyidentifiable information is removed. For example, a user's identity maybe treated so that no personally identifiable information can bedetermined for the user, or a user's geographic location may begeneralized where location information is obtained (such as to a city,ZIP code, or state level), so that a particular location of a usercannot be determined. Thus, the user may have control over howinformation is collected about the user and used by a content server.

User information that facilitates the sending of orders may be stored aswell in a user-account associated with voice requests. For instance, auser may provide passwords, credit card information, shippinginformation, and so on. This information may be sent with the orderafter an appropriate product is determined (whether by an automatedresponse system, by a human guide, or by a combination of the two).Users may be given the option to allow access to their information or tocertain pieces of their information. Additionally, the user may beprompted to confirm the purchase before it is finalized, or the user maybe given the option to automate the entire process.

As an example, a user may say “Buy a cooler for me that can holdtwenty-four cans of soda and that has wheels.” Further, user informationfor the requesting user may indicate a default shipping address, apreferred shipping carrier, and information for several of the user'scredit cards and an order of preference for using the cards. In anexample scenario, this request may be forwarded to a human guide who isprovided a guide user interface (UI) that displays the user informationand the voice request. The guide may find an appropriate cooler model,search for the lowest price for the model, determine a shipping methodwith the user's preferred carrier, and purchase the cooler from anappropriate vendor. The purchase may be conducted with the user'sprovided credit card information and shipped to the user's defaultshipping address.

In some examples, the process of identifying a target product or serviceand purchasing the target product or service may be separated. Forinstance, the user may first be able to determine an appropriate targetproduct or service for a particular request. Finding a target product orservice may be accomplished through a series of queries, possibly withthe help of a human guide. The user may then have the option to issue aseparate purchase request after a product or service has been found orcontinue searching for an alternative product or service.

II. HYBRID COMPUTER-AUTOMATED AND HUMAN RESPONSE SYSTEMS

FIG. 1 is a block diagram illustrating components of a system 100, inwhich an example embodiment may be implemented. System 100 includes aHybrid Computer-Automated and Human Response System 101 (which may bereferred to simply as a “hybrid response system”), client devices 102Aand 102B, and one or more communication networks 104.

A client device such as client device 102A or 102B may take variousforms, such as a mobile phone, a tablet computer, laptop computer, adesktop computer, or a wearable computer, among other possibilities. Inthe illustrated example, client device 102A is a head-mountable device(HMD), and client device 102B is a smartphone. Further, client devices102A and 102B may be configured to communicate with other devices viaone or more communication networks 104 via respective communicationlinks 103A and 103B.

Provided with network connectivity, a client device 102A or 102B maycommunicate with a hybrid response system 101. Further, client devices102A and 102B may each be configured to receive voice input, and togenerate or extract speech segments from the voice input. Further,client devices 102A and 102B may send potentially-actionable-speechmessages, which include such speech segments, to hybrid response system101 via one or more networks 104, such as the Internet, a cellularnetwork, and/or a service provider's network.

Note that herein, the term “speech segment” may refer to an audiosegment that includes speech by a user of a client device 102A or 102B,or to the speech-to-text transcription of such speech, or possibly to acombination of an audio segment with speech and a speech-to-texttranscription of such speech. Thus, a potentially-actionable-speechmessage may include an audio segment that includes speech by a user of aclient device 102A or 102B, and/or may include a speech-to-texttranscription of the speech in such an audio segment. Apotentially-actionable-speech message may also include otherinformation, such as context information related to the client deviceand/or a user-account that is currently associated with the clientdevice, for instance.

A client device 102A or 102B may provide various interface features thatallow a user to interact with a hybrid response system 101. Forinstance, HMD 302A may allow a user to provide an explicit indicationthat the user is about to provide speech that should be sent to thehybrid response system 101 in a potentially-actionable-speech message.As an example, when the user taps and holds a touchpad on HMD 302A, andsubsequently speaks, the subsequent speech may be captured as a speechsegment and sent to the hybrid response system in apotentially-actionable-speech message. Note that in this example, theHMD 302A may be configured to record speech after the user removes theirfinger from the touchpad, or may capture speech that occurs while stillthe user holds their finger on the touchpad. Client devices 102A and102B may also be configured to detect speech segments forpotentially-actionable-speech messages without explicit input from theuser; for example, by detecting words, a phrase, or phrases in speechthat are deemed to be potentially actionable.

In an example embodiment, the components of hybrid response system 101include an automated response system 106 and guide computing systems108A to 108C. Hybrid response system 101 and/or the components thereofmay be implemented in one or more computing clusters that are associatedwith an information-provider service. For example, the automatedresponse system 106 may include one or more computing systems that areconfigured to receive potentially-actionable-speech messages that aresent by client devices, and to analyze and potentially respond to suchmessages.

In a further aspect, automated response system 106 may apply one or moremachine-learning response processes to a speech segment, in order todetermine one or more potential responses to the speech segment. (Notethat a machine-learning response process may also be referred to as anartificial intelligence (AI) process.) A potential response that isgenerated by such an AI response process may be considered an“automated” response, since it is generated by a computing system,without the assistance of human input. Note that other automatedresponse process, which do not involve AI or machine-learning, are alsopossible.

Automated response system 106 may be further configured to determine aconfidence measure for each potential response that is generated by anautomated response process. Further, automated response system 106 maybe configured to determine if the confidence measure for a potentialresponse satisfies certain criteria (e.g., exceeds a threshold) and, ifthe criteria are satisfied, to select the potential response as aresponse to the actionable-speech message. Further, when there isacceptable confidence in an automated response, automated responsesystem 106 may be configured to send the automated response to theclient device 102A or 102B from which the correspondingactionable-speech message was received.

If automated response system 106 cannot determine an automated responseto a potentially-actionable-speech message with an acceptable level ofconfidence, then automated response system 106 may be configured to sendthe potentially-actionable-speech message, and/or a message containinginformation derived therefrom, to one or more guide computing systems108A to 108C. Note that automated response system 106 and guidecomputing systems 108A to 108C may be part of a service provider'snetwork, and may communicatively connected via wired or wireless links.Alternatively, some or all guide computing systems 108A to 108C may notbe part of the service provider's network. For example, third partyindividuals who are pre-qualified as guides may connect to automatedresponse system 106 via their home computers. In such an embodiment,automated response system 106 and guide computing systems 108A to 108Cmay communicate via one or more networks 104, such as the Internetand/or a cellular network.

Each guide computing system 108A to 108C may provide an interface viawhich a human can provide input. Such human input may be used togenerate a response to a potentially-actionable-speech message that wassent from a client device 102A or 102B.

For example, a guide computing system 108A to 108C may include or beconnected to a graphic display on which the guide computing system candisplay a graphical user interface (GUI) that facilitates ahuman-assisted response to a potentially-actionable-speech message. Sucha GUI may include the text of a speech segment and/or other informationthat may facilitate taking an action related to the speech segment. TheGUI may include features that prompt and/or receive human input, such astext and/or speech, via which a human guide can provide a responseand/or information that may be used to generate a response. The GUI mayalso include interactive features (e.g., buttons, check boxes, drop-downmenus, etc.) via which a human guide can provide a response and/orinformation that may be used to generate a response. Further, the GUImay include an interactive feature or features via which a human guidecan indicate that a response is acceptable and should be sent to theclient device 102A or 102B.

In some embodiments, the GUI may include a feature or features thatprovide a guide with context information that a user has elected to makeavailable via a user-account with the hybrid response system 101. Forexample, if a user has consented to use of certain information by thehybrid response system 101 (and associated human guides), such aslocation information, calendar information, contact information,information related to past interactions with contacts, and/or past useof certain applications, such information may selectively be provided inthe GUI when the user sends a potentially-actionable speech message fromtheir client device, in order to assist a guide in providing apersonalized response.

Further, in some cases, a user may link other user-accounts to theuser's account with the hybrid response system 101. For example, a usercould link their email accounts, social-network accounts, and/or othertypes of user-accounts, to their user-account with the hybrid responsesystem 101. In this scenario, a user may elect to allow full or partialaccess to such accounts to the hybrid response system (and possibly toassociated human guides as well). If the user elects to provide accessto such a linked account, then the GUI may include information obtainedvia the linked user-account, and/or may include a feature that allows aguide to access the linked user-account.

Generally, note that in situations where the systems discussed herecollect personal information about users, or may make use of personalinformation, the users may be provided with an opportunity to controlwhether programs or features collect user information (e.g., informationabout a user's social network, social actions or activities, profession,a user's preferences, or a user's current location), or to controlwhether and/or how to receive content from the content server that maybe more relevant to the user. In addition, certain data may be treatedin one or more ways before it is stored or used, so that personallyidentifiable information is removed. For example, a user's identity maybe treated so that no personally identifiable information can bedetermined for the user, or a user's geographic location may begeneralized where location information is obtained (such as to a city,ZIP code, or state level), so that a particular location of a usercannot be determined. Thus, the user may have control over howinformation is collected about the user and used by a content server.

In a further aspect of some embodiments, a guide computing system 108Ato 108C may provide a GUI or another type of interface via which a humanguide can send a communication to and/or establish a communicationsession with a client device 102A or 102B to which the guide isproviding a response. For example, a guide computing system 108A to 108Cmay include an interface that allows a human guide to initiate a phonecall to a client device 102A or 102B, initiate and/or engage in atext-based chat session with a client device 102A or 102B, send a textmessage (e.g., an SMS or MMS message) to a client device 102A or 102B,and/or send an e-mail to a client device, among other possibilities.Provided with such an interface, a guide may send a message or initiatea communication session to, e.g., request additional information tofacilitate and/or improve the quality of a response.

In the illustrated example, communication links 103A and 103B arewireless links. For example, a client device 102A or 102B may establishand communicate via a respective communication link 103A or 103B using awireless communication protocol, such as Bluetooth® radio technology,communication protocols described in IEEE 802.11 (including any IEEE802.11 revisions), and/or cellular communication protocols (such as GSM,CDMA, UMTS, EV-DO, WiMAX, or LTE), among other possibilities. Note,however, that a client device 102A or 102B may additionally oralternatively be configured for network communications over one or morewired connections. For example, a communication link 103A or 103B may bea wired serial bus such as a universal serial bus or a parallel bus. Awired connection may be a proprietary connection as well, or may takeother forms.

Variations on the system 100 illustrated in FIG. 1, and/or variations onthe functionality attributed to components of system 100, are possible.For instance, multiple components may be combined in the same entity. Asan example, a system may include more or less guide computing systemsthan shown in FIG. 1. Further, any component that is illustrated in FIG.1 may be divided into two or more components that collectively providethe described functionality. Other variations from the illustratedexamples are also possible.

FIG. 2 is a block diagram showing functional components of a system 200,according to an example embodiment. Collectively, the components ofsystem 200 may function to receive voice input (e.g., a speech segment),and to provide either an automated response or a human-assisted responseto the question.

More specifically, voice input 202 may be received by a transcriptionmodule 204, which applies a speech-to-text process to generate textcorresponding to the voice input 202. Further, transcription module 204may analyze whether the corresponding text is an accurate transcriptionof the voice input 202. In particular, the transcription module 204 maydetermine a translation confidence measure that indicates how likely itis that the corresponding text is an accurate transcription. If thetranslation confidence measure exceeds a threshold, then thetranscription module 204 may send the generated text to a categorizationmodule 206. If the translation confidence measure is lower (e.g., lessthan a threshold), then the transcription module 204 may send the text(and possibly audio data that includes some or all of the voice input202) to a guide computing system 208. Further, in some embodiments, ifthe confidence measure is very low (e.g., indicative of audio that doesnot include human speech), the transcription module 204 may discard thetext without taking any further action.

The guide computing system 208 may provide an interface that facilitatesevaluation of the generated text by a human guide. In particular, suchan interface may allow a human guide to indicate whether or not the textis an accurate translation. Further, such an interface may allow theguide to edit the text such that it is more accurate transcription ofthe voice input. In the event that a human guide indicates that the textis an accurate transcription, and/or edits the text such that it is anaccurate transcription, the guide computing system 208 may send the textto categorization module 206. Additionally or alternatively, andregardless of whether the text is an accurate transcription, the guidecomputing system 208 may provide an interface that allows the humanguide to indicate that the text does not include a question to which aresponse can be provided, and thus should be discarded instead of beingsent to categorization module 206.

The transcription module 204 or the guide computing system 208 may thusbe the component that outputs a potentially-actionable-speech message inwhich the speech segment includes text (and possibly an audio version ofthe text as well). As such, the transcription module could beimplemented at a client device, or could be implemented as part of aservice-provider's system. Alternatively, if the transcription module204 is implemented as part of a service provider's network, thetranscription module may receive and analyze apotentially-actionable-speech message that is sent from a client device.Further, the potentially-actionable-speech message may be sent to thecategorization module 206 for further evaluation.

Categorization module 206 may analyze whether the received text includesspeech to which a response can be provided (e.g., whether the speechsegment is, in fact, “actionable”). In particular, the categorizationmodule 206 may determine an actionable-speech confidence measure thatindicates how likely it is that the text constitutes a question, acommand, a request, or another type of message that is actionable. Ifthe actionable-speech confidence measure exceeds a threshold, then thecategorization module 206 may generate an actionable-speech message thatincludes some or all of the text, and send the actionable-speech messageto an automated response module 214.

Note that actionable speech segments may take various forms. Forexample, an actionable speech segment may be a question, such as “wherecan I get lunch right now?” An actionable speech segment could also be acommand or an instructions, such as “buy those shoes for me.” Anactionable speech segment may take other forms as well. Further, whilean actionable speech segment could make the desired response explicit,responsive actions may also be inferred from the speech segment and/orcontext information related to the client device and/or user-accountassociated with the speech segment.

In a further aspect, categorization module 206 may classify anactionable-speech message in various ways. For instance, categorizationmodule 206 may determine that a speech segment is of a particular type,relates to certain topic, and/or that providing a response to a speechsegment in the message has a certain difficulty level, among otherpossibilities. Accordingly, such classifications may be indicated in anactionable-speech message that is sent to automated response module 214.

If the actionable-speech confidence measure is lower (e.g., less than athreshold), then the categorization module 206 may send the generatedtext to a guide computing system 212. The guide computing system 212 mayprovide an interface that facilitates evaluation of the text by a humanguide. In particular, the guide computing system 212 may provide aninterface via which a human guide can indicate whether or not the textincludes a question, and possibly edit the question such that it is moreunderstandable. Further, the guide computing system 212 may provide aninterface for classifying actionable speech segments in the same or asimilar manner as a categorization module 206. Alternatively, once ahuman guide indicates that the text is actionable, the guide computingsystem 212 may send the text back to the categorization module 206,which may classify the speech segment and/or generate and send anactionable-speech message to automated response module 214.

Automated response module 214 may function to apply one or moreautomated processes to a given actionable-speech message, such as AI ormachine-learning processes. Each automated process may output a responseto the actionable-speech message, and a confidence score (i.e., ameasure of confidence) indicating a confidence that the response iscorrect. If the confidence score for a response from one AI process isabove a threshold at which the response is considered to be correct(e.g., greater than 99% confidence in the response), then this automatedresponse may be selected as the response to the question, and sent tothe corresponding client device.

Note that in some cases, there may be multiple responses having aconfidence score that is above the threshold where the response isconsidered to be correct. In this scenario, one of the “correct”responses may be selected and sent to the client device. For example,the correct response having the highest confidence score may beselected, or one of the correct responses may be selected at random. Asanother example, automated response module 214 may send some or all ofthe correct responses to a guide computing system 216 for evaluation bya human guide, who can then select one correct response. Othertechniques for selecting a response from multiple correct responses arepossible.

If no automated response to an actionable-speech message has aconfidence score above the threshold for a “correct” response, thenautomated response module 214 may forward the actionable-speech messageto a guide computing system 216. The guide computing system 216 maypresent the speech segment from the actionable-speech message and/orother information included in or derived from the actionable-speechmessage to a human guide. Further, guide computing system 216 mayprovide an interface that allows a human guide to indicate a response,provide information from which a response may be generated, and/orinitiate a responsive action.

In some embodiments, automated response module 214 may evaluate theconfidence score or scores for automated responses in a more granularway. For instance, automated response module 214 may classify responseswith one of three confidence levels: a high-confidence level (e.g.,greater than 99% confidence), a medium-confidence level (e.g., 80-98%confidence), and a low-confidence level (e.g., less than 80%). If one ormore automated responses are categorized as high-confidence responses,then automated response module 214 may initiated an automated response.

If there is no high-confidence automated response, then the informationthat is sent to the guide computing system may vary depending upon theconfidence level or levels of the automated responses. For example, ifall the automated responses have a low confidence level, then automatedresponse module 214 may simply send the actionable-speech message to aguide computing system 216. However, if some or all of the automatedresponses have a medium-confidence level, then automated response module214 may send the actionable-speech message and the medium-confidenceresponses to the guide computing system 216. The guide computing system216 may then provide an interface that allows a human guide to quicklyselect one of the medium-confidence responses as the correct response.Such an interface may also include features that allow a guide toprovide a response as they otherwise would, if the guide believes thatnone of the medium-confidence responses are correct.

Note that the feature of forwarding automated responses to guidecomputing systems may be applied in implementations other than thosedescribed above. In particular, when automated response module 214determines that a guide computing system 216 should make the ultimatedecision as to the correct response, automated response module 214 maysend any response that was determined by one of its AI processes to theguide computing system 216 for consideration by a human guide. In orderto facilitate a quicker response, automated response module 214 maylimit the number of automated responses that are sent to the guidecomputing system 216 for consideration. However, automated responsemodule 214 could theoretically send any number of automated responses toa guide computing system 216 for consideration.

Note that a response 218 may take various forms. For example, response218 may be content that is sent to a client device associated with theactionable-speech message. Such a response 218 may include text,hyperlinks, graphic content, and/or other types of information that canbe presented on a client device. A response 218 may also be a responsiveaction. For example, an AI process or guide computing system mayresponse to an actionable-speech message by purchasing items via anassociated user-account, or posting a message via an associated accounton a social network (presuming, in both cases, that the user hasauthorized such functionality). Other examples of responsive actions arealso possible. Further, note that depending upon a user's settings, theuser may or may not be notified explicitly (e.g., via e-mail or textmessage) of such responsive actions.

In a further aspect, automated response module 214 may receive feedbackfrom guide computing systems 208, 212 and/or 216, which may be used toimprove the AI processes that are applied to incoming actionable-speechmessages. Machine learning processes may then be applied to suchfeedback, so that the AI processes may improve over time. Note that assuch AI processes improve, this may free up human guides to respond tomore and more complex questions.

Automated response module 214 may use various types of feedback toimprove the one or more AI processes that are applied to incomingactionable-speech messages. For example, when an actionable-speechmessage is sent to a guide computing system 216, automated responsemodule may be informed of the human-assisted response that was sent tothe client device and/or the steps that the human took to determine theresponse. As another example, each time an automated response is sent toa guide computing system 216 for consideration, automated responsemodule 214 may be informed as to whether or not the automated responsewas selected as the correct response. As yet another example, when aclient device receives an automated response from automated responsemodule 214 or a human-assisted response from guide computing system 216,the client device may send feedback indicating the quality of theresponse. For instance, feedback from a client device may indicatewhether the response provided information they needed, whether or notthe response was correct, whether a better response could have beenprovided, and/or information that might improve future responses tosimilar questions, among other possibilities.

In a further aspect, system 200 may include a latency estimation module210. The latency estimation module 210 may evaluate questions andestimate how long it will take for a response to be provided to a clientdevice. Latency estimation module 210 may therefore be configured tosend an estimated response-time message to a client device that isawaiting the response. The estimated response time message may indicatean estimated period of time (e.g., 30 seconds) until the client devicewill receive a response to a question that was sent from the clientdevice. Further, while a client device is awaiting a response, latencyestimation module 210 may update the estimated response time, and sendestimated response-time message indicating such updates, as newinformation is received.

In order to estimate and/or update the estimated response time, latencyestimation module 210 may receive information from transcription module204, categorization module 206, automated response module 214, guidecomputing systems, and/or other sources. For example, latency estimationmodule 210 may increase or decrease an estimated response time for aactionable-speech message depending on: (a) whether the transcriptionmodule 204 has a lower or higher confidence in a transcription,respectively, (b) whether the categorization module 206 has a higher orlower confidence that the received text is actionable, (c) thecomplexity of the speech segment and/or the type or category of speechsegment (e.g., as determined by categorization module 206), and/or (d)whether or not automated response module can provide an automatedresponse with a high enough level of confidence, among otherpossibilities.

Note that some or all of guide computing systems 208, 212, 216 may bethe same guide computing system. Alternatively, different guidecomputing systems may be utilized for some or all of the guide computingsystems that may be involved in providing a response to a particularactionable-speech message.

Further, in some embodiments, all of the modules shown in FIG. 2 may bepart of an automated response system 106. In other embodiments, some ofthe modules shown in FIG. 2 may be implemented at a client device 102Aor 102B. For example, transcription module 204 and/or categorizationmodule 206 may be implemented by a client device. Other examples arealso possible.

III. EXAMPLE WEARABLE COMPUTING DEVICES

Systems and devices in which example embodiments may be implemented willnow be described in greater detail. In general, an example system may beimplemented in or may take the form of a wearable computer (alsoreferred to as a wearable computing device). In an example embodiment, awearable computer takes the form of or includes a head-mountable device(HMD).

An example system may also be implemented in or take the form of otherdevices, such as a mobile phone, among other possibilities. Further, anexample system may take the form of non-transitory computer readablemedium, which has program instructions stored thereon that areexecutable by at a processor to provide the functionality describedherein. An example system may also take the form of a device such as awearable computer or mobile phone, or a subsystem of such a device,which includes such a non-transitory computer readable medium havingsuch program instructions stored thereon.

An HMD may generally be any display device that is capable of being wornon the head and places a display in front of one or both eyes of thewearer. An HMD may take various forms such as a helmet or eyeglasses. Assuch, references to “eyeglasses” or a “glasses-style” HMD should beunderstood to refer to an HMD that has a glasses-like frame so that itcan be worn on the head. Further, example embodiments may be implementedby or in association with an HMD with a single display or with twodisplays, which may be referred to as a “monocular” HMD or a “binocular”HMD, respectively.

FIG. 3A illustrates a wearable computing system according to an exampleembodiment. In FIG. 3A, the wearable computing system takes the form ofa head-mountable device (HMD) 302 (which may also be referred to as ahead-mounted display). It should be understood, however, that examplesystems and devices may take the form of or be implemented within or inassociation with other types of devices, without departing from thescope of the invention. As illustrated in FIG. 3A, the HMD 302 includesframe elements including lens-frames 304, 306 and a center frame support308, lens elements 310, 312, and extending side-arms 314, 316. Thecenter frame support 308 and the extending side-arms 314, 316 areconfigured to secure the HMD 302 to a user's face via a user's nose andears, respectively.

Each of the frame elements 304, 306, and 108 and the extending side-arms314, 316 may be formed of a solid structure of plastic and/or metal, ormay be formed of a hollow structure of similar material so as to allowwiring and component interconnects to be internally routed through theHMD 302. Other materials may be possible as well.

One or more of each of the lens elements 310, 312 may be formed of anymaterial that can suitably display a projected image or graphic. Each ofthe lens elements 310, 312 may also be sufficiently transparent to allowa user to see through the lens element. Combining these two features ofthe lens elements may facilitate an augmented reality or heads-updisplay where the projected image or graphic is superimposed over areal-world view as perceived by the user through the lens elements.

The extending side-arms 314, 316 may each be projections that extendaway from the lens-frames 304, 306, respectively, and may be positionedbehind a user's ears to secure the HMD 302 to the user. The extendingside-arms 314, 316 may further secure the HMD 302 to the user byextending around a rear portion of the user's head. Additionally oralternatively, for example, the HMD 302 may connect to or be affixedwithin a head-mounted helmet structure. Other configurations for an HMDare also possible.

The HMD 302 may also include an on-board computing system 318, an imagecapture device 320, a sensor 322, and a finger-operable touch pad 324.The on-board computing system 318 is shown to be positioned on theextending side-arm 314 of the HMD 302; however, the on-board computingsystem 318 may be provided on other parts of the HMD 302 or may bepositioned remote from the HMD 302 (e.g., the on-board computing system318 could be wire- or wirelessly-connected to the HMD 302). The on-boardcomputing system 318 may include a processor and memory, for example.The on-board computing system 318 may be configured to receive andanalyze data from the image capture device 320 and the finger-operabletouch pad 324 (and possibly from other sensory devices, user interfaces,or both) and generate images for output by the lens elements 310 and312.

The image capture device 320 may be, for example, a camera that isconfigured to capture still images and/or to capture video. In theillustrated configuration, image capture device 320 is positioned on theextending side-arm 314 of the HMD 302; however, the image capture device320 may be provided on other parts of the HMD 302. The image capturedevice 320 may be configured to capture images at various resolutions orat different frame rates. Many image capture devices with a smallform-factor, such as the cameras used in mobile phones or webcams, forexample, may be incorporated into an example of the HMD 302.

Further, although FIG. 3A illustrates one image capture device 320, moreimage capture device may be used, and each may be configured to capturethe same view, or to capture different views. For example, the imagecapture device 320 may be forward facing to capture at least a portionof the real-world view perceived by the user. This forward facing imagecaptured by the image capture device 320 may then be used to generate anaugmented reality where computer generated images appear to interactwith or overlay the real-world view perceived by the user.

The sensor 322 is shown on the extending side-arm 316 of the HMD 302;however, the sensor 322 may be positioned on other parts of the HMD 302.For illustrative purposes, only one sensor 322 is shown. However, in anexample embodiment, the HMD 302 may include multiple sensors. Forexample, an HMD 302 may include sensors 302 such as one or moregyroscopes, one or more accelerometers, one or more magnetometers, oneor more light sensors, one or more infrared sensors, and/or one or moremicrophones. Other sensing devices may be included in addition or in thealternative to the sensors that are specifically identified herein.

The finger-operable touch pad 324 is shown on the extending side-arm 314of the HMD 302. However, the finger-operable touch pad 324 may bepositioned on other parts of the HMD 302. Also, more than onefinger-operable touch pad may be present on the HMD 302. Thefinger-operable touch pad 324 may be used by a user to input commands.The finger-operable touch pad 324 may sense at least one of a pressure,position and/or a movement of one or more fingers via capacitivesensing, resistance sensing, or a surface acoustic wave process, amongother possibilities. The finger-operable touch pad 324 may be capable ofsensing movement of one or more fingers simultaneously, in addition tosensing movement in a direction parallel or planar to the pad surface,in a direction normal to the pad surface, or both, and may also becapable of sensing a level of pressure applied to the touch pad surface.In some embodiments, the finger-operable touch pad 324 may be formed ofone or more translucent or transparent insulating layers and one or moretranslucent or transparent conducting layers. Edges of thefinger-operable touch pad 324 may be formed to have a raised, indented,or roughened surface, so as to provide tactile feedback to a user whenthe user's finger reaches the edge, or other area, of thefinger-operable touch pad 324. If more than one finger-operable touchpad is present, each finger-operable touch pad may be operatedindependently, and may provide a different function.

In a further aspect, HMD 302 may be configured to receive user input invarious ways, in addition or in the alternative to user input receivedvia finger-operable touch pad 324. For example, on-board computingsystem 318 may implement a speech-to-text process and utilize a syntaxthat maps certain spoken commands to certain actions. In addition, HMD302 may include one or more microphones via which a wearer's speech maybe captured. Configured as such, HMD 302 may be operable to detectspoken commands and carry out various computing functions thatcorrespond to the spoken commands.

As another example, HMD 302 may interpret certain head-movements as userinput. For example, when HMD 302 is worn, HMD 302 may use one or moregyroscopes and/or one or more accelerometers to detect head movement.The HMD 302 may then interpret certain head-movements as being userinput, such as nodding, or looking up, down, left, or right. An HMD 302could also pan or scroll through graphics in a display according tomovement. Other types of actions may also be mapped to head movement.

As yet another example, HMD 302 may interpret certain gestures (e.g., bya wearer's hand or hands) as user input. For example, HMD 302 maycapture hand movements by analyzing image data from image capture device320, and initiate actions that are defined as corresponding to certainhand movements.

As a further example, HMD 302 may interpret eye movement as user input.In particular, HMD 302 may include one or more inward-facing imagecapture devices and/or one or more other inward-facing sensors (notshown) sense a user's eye movements and/or positioning. As such, certaineye movements may be mapped to certain actions. For example, certainactions may be defined as corresponding to movement of the eye in acertain direction, a blink, and/or a wink, among other possibilities.

HMD 302 also includes a speaker 325 for generating audio output. In oneexample, the speaker could be in the form of a bone conduction speaker,also referred to as a bone conduction transducer (BCT). Speaker 325 maybe, for example, a vibration transducer or an electroacoustic transducerthat produces sound in response to an electrical audio signal input. Theframe of HMD 302 may be designed such that when a user wears HMD 302,the speaker 325 contacts the wearer. Alternatively, speaker 325 may beembedded within the frame of HMD 302 and positioned such that, when theHMD 302 is worn, speaker 325 vibrates a portion of the frame thatcontacts the wearer. In either case, HMD 302 may be configured to sendan audio signal to speaker 325, so that vibration of the speaker may bedirectly or indirectly transferred to the bone structure of the wearer.When the vibrations travel through the bone structure to the bones inthe middle ear of the wearer, the wearer can interpret the vibrationsprovided by BCT 325 as sounds.

Various types of bone-conduction transducers (BCTs) may be implemented,depending upon the particular implementation. Generally, any componentthat is arranged to vibrate the HMD 302 may be incorporated as avibration transducer. Yet further it should be understood that an HMD302 may include a single speaker 325 or multiple speakers. In addition,the location(s) of speaker(s) on the HMD may vary, depending upon theimplementation. For example, a speaker may be located proximate to awearer's temple (as shown), behind the wearer's ear, proximate to thewearer's nose, and/or at any other location where the speaker 325 canvibrate the wearer's bone structure.

FIG. 3B illustrates an alternate view of the wearable computing deviceillustrated in FIG. 3A. As shown in FIG. 3B, the lens elements 310, 312may act as display elements. The HMD 302 may include a first projector328 coupled to an inside surface of the extending side-arm 316 andconfigured to project a display 330 onto an inside surface of the lenselement 312. Additionally or alternatively, a second projector 332 maybe coupled to an inside surface of the extending side-arm 314 andconfigured to project a display 334 onto an inside surface of the lenselement 310.

The lens elements 310, 312 may act as a combiner in a light projectionsystem and may include a coating that reflects the light projected ontothem from the projectors 328, 332. In some embodiments, a reflectivecoating may not be used (e.g., when the projectors 328, 332 are scanninglaser devices).

In alternative embodiments, other types of display elements may also beused. For example, the lens elements 310, 312 themselves may include: atransparent or semi-transparent matrix display, such as anelectroluminescent display or a liquid crystal display, one or morewaveguides for delivering an image to the user's eyes, or other opticalelements capable of delivering an in focus near-to-eye image to theuser. A corresponding display driver may be disposed within the frameelements 304, 306 for driving such a matrix display. Alternatively oradditionally, a laser or LED source and scanning system could be used todraw a raster display directly onto the retina of one or more of theuser's eyes. Other possibilities exist as well.

FIG. 3C illustrates another wearable computing system according to anexample embodiment, which takes the form of an HMD 352. The HMD 352 mayinclude frame elements and side-arms such as those described withrespect to FIGS. 3A and 3B. The HMD 352 may additionally include anon-board computing system 354 and an image capture device 356, such asthose described with respect to FIGS. 3A and 3B. The image capturedevice 356 is shown mounted on a frame of the HMD 352. However, theimage capture device 356 may be mounted at other positions as well.

As shown in FIG. 3C, the HMD 352 may include a single display 358 whichmay be coupled to the device. The display 358 may be formed on one ofthe lens elements of the HMD 352, such as a lens element described withrespect to FIGS. 3A and 3B, and may be configured to overlaycomputer-generated graphics in the user's view of the physical world.The display 358 is shown to be provided in a center of a lens of the HMD352, however, the display 358 may be provided in other positions, suchas for example towards either the upper or lower portions of thewearer's field of view. The display 358 is controllable via thecomputing system 354 that is coupled to the display 358 via an opticalwaveguide 360.

FIG. 3D illustrates another wearable computing system according to anexample embodiment, which takes the form of a monocular HMD 372. The HMD372 may include side-arms 373, a center frame support 374, and a bridgeportion with nosepiece 375. In the example shown in FIG. 3D, the centerframe support 374 connects the side-arms 373. The HMD 372 does notinclude lens-frames containing lens elements. The HMD 372 mayadditionally include a component housing 376, which may include anon-board computing system (not shown), an image capture device 378, anda button 379 for operating the image capture device 378 (and/or usablefor other purposes). Component housing 376 may also include otherelectrical components and/or may be electrically connected to electricalcomponents at other locations within or on the HMD. HMD 372 alsoincludes a BCT 386.

The HMD 372 may include a single display 380, which may be coupled toone of the side-arms 373 via the component housing 376. In an exampleembodiment, the display 380 may be a see-through display, which is madeof glass and/or another transparent or translucent material, such thatthe wearer can see their environment through the display 380. Further,the component housing 376 may include the light sources (not shown) forthe display 380 and/or optical elements (not shown) to direct light fromthe light sources to the display 380. As such, display 380 may includeoptical features that direct light that is generated by such lightsources towards the wearer's eye, when HMD 372 is being worn.

In a further aspect, HMD 372 may include a sliding feature 384, whichmay be used to adjust the length of the side-arms 373. Thus, slidingfeature 384 may be used to adjust the fit of HMD 372. Further, an HMDmay include other features that allow a wearer to adjust the fit of theHMD, without departing from the scope of the invention.

FIGS. 3E to 3G are simplified illustrations of the HMD 372 shown in FIG.3D, being worn by a wearer 390. As shown in FIG. 3F, when HMD 372 isworn, BCT 386 is arranged such that when HMD 372 is worn, BCT 386 islocated behind the wearer's ear. As such, BCT 386 is not visible fromthe perspective shown in FIG. 3E.

In the illustrated example, the display 380 may be arranged such thatwhen HMD 372 is worn, display 380 is positioned in front of or proximateto a user's eye when the HMD 372 is worn by a user. For example, display380 may be positioned below the center frame support and above thecenter of the wearer's eye, as shown in FIG. 3E. Further, in theillustrated configuration, display 380 may be offset from the center ofthe wearer's eye (e.g., so that the center of display 380 is positionedto the right and above of the center of the wearer's eye, from thewearer's perspective).

Configured as shown in FIGS. 3E to 3G, display 380 may be located in theperiphery of the field of view of the wearer 390, when HMD 372 is worn.Thus, as shown by FIG. 3F, when the wearer 390 looks forward, the wearer390 may see the display 380 with their peripheral vision. As a result,display 380 may be outside the central portion of the wearer's field ofview when their eye is facing forward, as it commonly is for manyday-to-day activities. Such positioning can facilitate unobstructedeye-to-eye conversations with others, as well as generally providingunobstructed viewing and perception of the world within the centralportion of the wearer's field of view. Further, when the display 380 islocated as shown, the wearer 390 may view the display 380 by, e.g.,looking up with their eyes only (possibly without moving their head).This is illustrated as shown in FIG. 3G, where the wearer has movedtheir eyes to look up and align their line of sight with display 380. Awearer might also use the display by tilting their head down andaligning their eye with the display 380.

FIG. 4 is a simplified block diagram a computing device 410 according toan example embodiment. In an example embodiment, device 410 communicatesusing a communication link 420 (e.g., a wired or wireless connection) toa remote device 430. The device 410 may be any type of device that canreceive data and display information corresponding to or associated withthe data. For example, the device 410 may take the form of or include ahead-mountable display, such as the head-mounted devices 302, 352, or372 that are described with reference to FIGS. 3A to 3G.

The device 410 may include a processor 414 and a display 416. Thedisplay 416 may be, for example, an optical see-through display, anoptical see-around display, or a video see-through display. Theprocessor 414 may receive data from the remote device 430, and configurethe data for display on the display 416. The processor 414 may be anytype of processor, such as a micro-processor or a digital signalprocessor, for example.

The device 410 may further include on-board data storage, such as memory418 coupled to the processor 414. The memory 418 may store software thatcan be accessed and executed by the processor 414, for example.

The remote device 430 may be any type of computing device or transmitterincluding a laptop computer, a mobile telephone, head-mountable display,tablet computing device, etc., that is configured to transmit data tothe device 410. The remote device 430 and the device 410 may containhardware to enable the communication link 420, such as processors,transmitters, receivers, antennas, etc.

Further, remote device 430 may take the form of or be implemented in acomputing system that is in communication with and configured to performfunctions on behalf of client device, such as computing device 410. Sucha remote device 430 may receive data from another computing device 410(e.g., an HMD 302, 352, or 372 or a mobile phone), perform certainprocessing functions on behalf of the device 410, and then send theresulting data back to device 410. This functionality may be referred toas “cloud” computing.

In FIG. 4, the communication link 420 is illustrated as a wirelessconnection; however, wired connections may also be used. For example,the communication link 420 may be a wired serial bus such as a universalserial bus or a parallel bus. A wired connection may be a proprietaryconnection as well. The communication link 420 may also be a wirelessconnection using, e.g., Bluetooth® radio technology, communicationprotocols described in IEEE 802.11 (including any IEEE 802.11revisions), Cellular technology (such as GSM, CDMA, UMTS, EV-DO, WiMAX,or LTE), or Zigbee® technology, among other possibilities. The remotedevice 430 may be accessible via the Internet and may include acomputing cluster associated with a particular web service (e.g.,social-networking, photo sharing, address book, etc.).

IV. ILLUSTRATIVE METHODS

FIG. 5 is a flow chart illustrating a method 500, according to anexample embodiment. Method 500 may be carried out to enable users topurchase a product or service via a voice request received by a hybridresponse system, where the voice request is associated with auser-account. Method 500 may be carried out by hybrid response system asdescribed above.

Method 500 involves a hybrid response system receiving a firstspeech-segment message, where the first speech-segment message comprisesa speech segment, and where the first speech-segment message isassociated with a user-account, as shown by block 502. The hybridresponse system determines that the speech segment indicates a purchaserequest, as shown by block 504. The hybrid response system thendetermines a target product or service based on at least the purchaserequest, as shown by block 506, and the hybrid response systemdetermines a confidence level associated with a purchase of the targetproduct or service, as shown by block 508. If the confidence level isgreater than or equal to a threshold level, then the hybrid responsesystem sends a purchase order, via the associated user-account, for thetarget product or service, as shown in block 510. Otherwise, if theconfidence level is less than the threshold level, then the hybridresponse system sends the purchase request and the target product orservice to at least one guide computing system to facilitate a responseto the purchase request by the at least one guide computing system, asshown in block 512.

At block 502, the speech segment message may include a request for apurchase or a command to buy a product or a service. For example, a usermay state “Buy product X for me,” or “Buy service Y for me.” In order tohelp ensure that the request or command is intended, the user may holddown a button or tap-and-hold on a touchpad of the client device beforespeaking the request (and possibly continuing to press the button orkeep their finger on the touchpad for the duration of the voicerequest), for example. Alternatively, a user may specifically the clientdevice at the beginning of the voice request, for example, “Ok phone,buy product X for me.” Other example commands or requests may include“Reserve Hotel X in Hawaii arriving December 1^(st) and departingDecember 8^(th) for me,” “Book a flight to Hawaii for me on airline Yleaving December 1^(st) and returning December 8^(th) for me” or “Rent afour-door sedan for me in Hawaii beginning on December 1^(st) and endingDecember 8^(th).” Accordingly, the target product or service may includeconsumer goods, gift certificates, plane tickets, hotel reservations,car rentals, among other possibilities.

In some embodiments, at block 512, the at least one guide computingsystem determines whether the target product or service is responsive tothe purchase request. If the target product or service is responsive tothe purchase request, then the at least one guide computing system sendsa purchase order for the target product or service. Otherwise, if thetarget product or service is not responsive to the purchase request, theat least one guide computing system determines a second target productor service based on at least the purchase request and the at least oneguide computing system sends a purchase order for the second targetproduct or service.

In various embodiments, the method 500 further involves the hybridresponse system receiving an image. In this case, at block 506, thehybrid response system determines the target product or service basedfurther on the image, the details of which are further discussed belowwith respect to FIG. 6.

In some embodiments, block 506 further involves the hybrid responsesystem determining the target product or service further based on one ormore predetermined user preferences. The user preferences may be set bythe user-account associated with the purchase request or speech segment.These user preferences may include selecting the target product orservice based on the lowest price available, specified stores or serviceproviders or preferred brands, among other possibilities.

In other embodiments, the method 500 further involves, at block 506, thehybrid response system determining the target product or service isfurther based on one or more previous purchases made via the associateduser-account. For example, the hybrid response system may determine fromprevious purchases that a user prefers a certain type of good (e.g.,prefers two-ply toilet paper, instead of single-ply), prefers certainbrands or prefers to purchase via a certain account associated with theuser even if the price is not the lowest for a given product or service.In another example, if the speech segment or request is “Buy a powercord for me,” the hybrid response system may determine that the userrecently purchased a certain brand of tablet or mobile phone anddetermine an appropriate model for the target power cord.

In still further embodiments, the method 500 may further involve, atblock 506, the hybrid response system determining the target product orservice further based on one or more discounts associated with thepurchase request. These discounts may include free shipping, onlinesales, and/or loyalty reward points for shopping at a given store, amongother possibilities.

In some embodiments, at block 510 or 512, the purchase order comprisesuser data from the associated user-account. The user data may includecredit card information, a loyalty reward number, a user account numberor login details associated with the online store or service provider,shipping preferences (e.g., rush delivery at a cost or free standarddelivery and/or a preferred carrier), among other possibilities. Infurther embodiments, the user data from the associated user-account maybe derived from a linked user-account that is a separate purchasingaccount, such as Google Wallet, that has information stored specificallyfor purchases (e.g., credit card information, purchase history,purchasing preferences, among other possibilities).

In some embodiments, the method 500 may further involve, at block 506,the at least one guide computing system determining whether the targetproduct or service is responsive to the purchase request comprisessending a target-product-or-service-detail request. Exampletarget-product-or-service-detail requests may include a request forfurther product or service details, such as clothing size, color, datesfor service, among other possibilities.

In other embodiments, method 500 may further involve the hybrid responsesystem sending a purchase-approval request. The purchase-approvalrequest may include an identification of the target product or service,the price of the product or service, the vendor, the price of shipping,the shipping carrier, and/or the estimated arrival date, among otherpossibilities. If the user is satisfied with the details of thepurchase-approval request, the user may then speak a command, such as“buy,” that is sent to the hybrid response system.

In some embodiments, method 500 may further involve the hybrid responsesystem sending a confirmation-of-purchase message. The client devicereceives the confirmation-of-purchase message, which may include atracking number, a confirmation number, and/or a message indicating thepurchase is complete, among other possibilities. In some embodiments,the confirmation-of-purchase message may include a countdown timerallowing the user a window of time in which to cancel or modify thepurchase order.

FIG. 6 is a flow chart illustrating a method 600, according to anexample embodiment. Method 600 may be carried out to enable users topurchase a product or service via a voice request received by a clientdevice, where the client device is associated with a user-account. Forexample, method 600 may be carried out by an HMD, or a system therein(e.g., a processor and non-transitory computer readable medium withinstructions that are executable to carry out the functionalitydescribed herein). Method 600 could be also be carried out by othertypes of client devices, such as a mobile phone, tablet computer, orpersonal computer, among other possibilities.

Method 600 involves a client device receiving a first speech segment,where the first speech segment comprises a purchase request and wherethe client device is associated with a user-account, as shown in block602. The client device then receives an image, where the image comprisesat least one target-product-or-service detail, as shown in block 604.Next the client device determines a target product or service based onat least the purchase request, as shown in block 606, and the clientdevice determines a confidence level associated with a purchase of thetarget product or service, as shown in block 608. If the confidencelevel is greater than or equal to a threshold level, then the clientdevice sends a purchase order, via the associated user-account, for thetarget product or service, as shown in block 610. Otherwise, if theconfidence level is less than the threshold level, then (i) the clientdevice sends a purchase-request message comprising the purchase requestand the image, shown at block 612, (ii) the client device receives atarget-product-or-service identification message comprising a secondtarget product or service, shown at block 614, and (iii) the clientdevice sends a purchase order for the second target product or service,shown at block 616.

The method 600 may be performed using the embodiments described withrespect to method 500 above.

In some embodiments, at block 604, the image may be captured by a cameraon a client device, for example. More specifically, an HMD may have aPOV camera that is capable of sending an image or video feed to thehybrid response system, where the image or video is indicative of whatthe wearer is looking at. Sending the image may occur automatically inassociation with the voice request or specifically at the instruction ofthe user. In either case, the image feed may scan for a bar code, useobject recognition, or simply relay the image feed to a guide computingsystem to assist a guide in determining a target product or service. Insome embodiments, the image may comprise contextual details related tothe purchase request including, for example, at least a portion of thetarget product, an advertisement, a product label, product packaging,and/or a UPC bar code.

In some embodiments, the method 600 may further involve the clientdevice determining the target product or service is further based on oneor more predetermined user-preferences, as described above.

In some embodiments, the method 600 may further involve the clientdevice determining the target product or service is further based on oneor more previous purchases made via the associated user-account, also asdescribed above.

In some embodiments, the method 600 may further involve the clientdevice determining the target product or service is further based on oneor more discounts associated with the purchase request, also asdescribed above.

In some embodiments, the method 600 may further involve the clientdevice receiving a target-product-or-service-detail request and theclient device then sending a second speech segment comprisinginformation related to the purchase request or a second image comprisinga second target-product-or-service detail. An example second speechsegment may include further product or service details, such as clothingsize, color, or dates for service, among other possibilities.

In some embodiments, the method 600 may involve the client devicereceiving a confirmation-of-purchase message, as described above.

V. ILLUSTRATIVE APPLICATIONS

FIG. 7 is another illustration of screens from an HMD display, inaccordance with an illustrative application of an example embodiment. Inparticular, FIG. 7 illustrates another scenario where an HMD user sendsa first speech segment or purchase request to a hybrid response system.Note that the screens 701, 702, 704, 706, and 708 may be representativeof screen shots, and may appear in the order that they might occur, inaccordance with an example embodiment. As such, the approximate times T₀to T₄ at which each screen 701, 702, 704, 706, and 708 might bedisplayed is indicated on a timeline 720.

As shown at time T₀, the HMD may display a home screen 701. And, an HMDuser may initiate a voice request from the home screen 701 by tappingand holding a touchpad on their HMD, and then speaking the voicerequest. In the scenario illustrated in FIG. 7, the voice request is:“Buy the Brand X basketball shoes for me.” When this voice request isreceived by the HMD, the HMD may apply a speech-to-text process to thevoice request. The HMD may then display an initial request card, whichincludes a transcription of the spoken voice request (e.g., the literaltranscription of the spoken words), along with an indication that therequest is being sent to the hybrid response system. Thus, as shown attime T₁, the HMD may display a screen 702 with an initial request card703 that indicates: “Sending: ‘Buy the Brand X basketball shoes forme.’”

Further, at some time T₂ between transmission of the initial requestcard and receipt of a response, the HMD may display a screen 704 thatincludes a status card 705. The status card 705 indicates that theestimated wait time for a response from the hybrid response system istwo minutes. Further, status card 705 indicates that the hybrid responsesystem is “Looking for places to buy brand X basketball shoes in men'ssize 11.” Note that the voice request indicated in the status card 705may have been personalized based on user-account information that theuser opted to make available to the hybrid response system. Inparticular, an automated process or a guide computing system may havedetermined from such account information (e.g., past purchases and/orstored purchasing preferences) that the particular user wears size 11shoes.

As further shown in FIG. 7, the HMD may receive a response to the voicerequest from a hybrid response system and, at time T₃, may display ascreen 706 with a response card 707. In the illustrated example,response card 707 indicates: “Brand X model 1 basketball shoes areavailable for $99.99 with free shipping from the Yangtze online store.Speak “buy” to purchase.” In this example, a user speaks “buy,” sendinga purchase approval response to the hybrid response system.

In some embodiments, it is also possible that one or more additionalinputs, such as a response to a product-or-service-detail request, maybe required to confirm a purchase. In the scenario shown in FIG. 7, theresponse from the guide computing system may be selected based oncontext information associated with the HMD, user preferences, and/orinformation from an associated user-account. For example, based on suchinformation, a guide computing system may be fairly confident that theuser wants to purchase Brand X model 1 basketball shoes. However, theguide may be uncertain as to the particular store where the user wouldlike to make the purchase and therefore send the client device aproduct-or-service-detail request.

As further shown in FIG. 7, the HMD may receive a confirmation messagefrom the hybrid response system and, at time T₄, may display a screen708 with a confirmation card 709. In the illustrated example, responsecard 709 indicates: “Purchase confirmed. Shipping via FedEx to arrive byFebruary 2nd. Tracking No. XYZ123.”

VI. CONCLUSION

In the figures, similar symbols typically identify similar components,unless context indicates otherwise. The illustrative embodimentsdescribed in the detailed description, figures, and claims are not meantto be limiting. Other embodiments can be utilized, and other changes canbe made, without departing from the scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, blockand/or communication may represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, functionsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages may be executed out of order from that shownor discussed, including in substantially concurrent or in reverse order,depending on the functionality involved. Further, more or fewer steps,blocks and/or functions may be used with any of the message flowdiagrams, scenarios, and flow charts discussed herein, and these messageflow diagrams, scenarios, and flow charts may be combined with oneanother, in part or in whole.

A step or block that represents a processing of information maycorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information may correspond to a module, a segment, or aportion of program code (including related data). The program code mayinclude one or more instructions executable by a processor forimplementing specific logical functions or actions in the method ortechnique. The program code and/or related data may be stored on anytype of computer-readable medium, such as a storage device, including adisk drive, a hard drive, or other storage media.

The computer-readable medium may also include non-transitorycomputer-readable media such as computer-readable media that stores datafor short periods of time like register memory, processor cache, and/orrandom access memory (RAM). The computer-readable media may also includenon-transitory computer-readable media that stores program code and/ordata for longer periods of time, such as secondary or persistent longterm storage, like read only memory (ROM), optical or magnetic disks,and/or compact-disc read only memory (CD-ROM), for example. Thecomputer-readable media may also be any other volatile or non-volatilestorage systems. A computer-readable medium may be considered acomputer-readable storage medium, for example, or a tangible storagedevice.

Moreover, a step or block that represents one or more informationtransmissions may correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions may be between software modules and/orhardware modules in different physical devices.

We claim:
 1. A method, comprising: receiving, by a computing system, aspeech segment, wherein the first speech-segment message is associatedwith a user-account; determining, by the computing system, a translationof the speech segment; determining, by the computing system, atranslation confidence level associated with the translation; if thetranslation confidence level is greater or equal to a translationthreshold level, determining, by the computing system, an actionablemessage from the translation, including determining that the actionablemessage indicates a purchase request; determining, by the computingsystem, an actionable-message confidence level associated with theactionable message; if the actionable-message confidence level isgreater or equal to an actionable-message threshold level, providing, bythe computing system, a first determination of a target product orservice in the purchase request; determining, by the computing system, apurchase-request confidence level associated with the firstdetermination of the target product or service; if the purchase-requestconfidence level is greater than or equal to a purchase-requestthreshold level, purchasing, by the computing system, the target productor service via the associated user-account; and otherwise, if thepurchase-request confidence level is less than the purchase-requestthreshold level, sending, by the computing system, the speech segment toat least one guide computing system, the at least one guide systemconfigured to receive input relating to the speech segment or thepurchase request, provide a second determination of the target productor service based on the input, and purchase the target product orservice via the associated user-account.
 2. The method of claim 1,further comprising: receiving an image at the computing system, whereinthe image comprises contextual details related to the purchase request,wherein the first determination of the target product or service isfurther based on the image.
 3. The method of claim 2, wherein the imagecomprises at least a portion of the target product, an advertisement, aproduct label, product packaging, and/or a UPC bar code.
 4. The methodof claim 1, wherein the first determination of the target product orservice is further based on one or more predetermined user preferences.5. The method of claim 1, wherein the first determination of the targetproduct or service is further based on one or more previous purchasesmade via the associated user-account.
 6. The method of claim 1, whereinthe first determination of the target product or service is furtherbased on one or more discounts associated with the purchase request. 7.The method of claim 1, wherein the at least one guide computing systemis further configured to send a target-product-or-service-detail requestto a client device requesting details on the target product or service,and the input for the second determination of the target product orservice includes the details provided by client device.
 8. The method ofclaim 1, further comprising: sending, by the computing system, apurchase-approval request.
 9. The method of claim 1, further comprising:sending, by the computing system, a confirmation-of-purchase message.10. The method of claim 1, wherein the first determination of the targetproduct or service provided by the computing system is the same as thesecond determination of the target product or service provided by the atleast one guide system.
 11. The method of claim 1, wherein the firstdetermination of the target product or service provided by the computingsystem is different from the second determination of the target productor service provided by the at least one guide system.
 12. The method ofclaim 1, wherein the input for providing the second determination of thetarget product or service includes at least one of an image withcontextual details related to the purchase request, one or morepredetermined user preferences, one or more previous purchases made viathe associated user-account, or one or more discounts associated withthe purchase request.
 13. A non-transitory machine-readable storagemedium comprising instructions that, when executed by one or moreprocessors of a machine, cause the machine to perform operationscomprising: receiving a speech segment, wherein the first speech-segmentmessage is associated with a user-account; determining a translation ofthe speech segment; determining a translation confidence levelassociated with the translation; if the translation confidence level isgreater or equal to a translation threshold level, determining anactionable message from the translation, including determining that theactionable message indicates a purchase request; determining anactionable-message confidence level associated with the actionablemessage; if the actionable-message confidence level is greater or equalto an actionable-message threshold level, providing a firstdetermination of a target product or service in the purchase request;determining a purchase-request confidence level associated with thefirst determination of the target product or service; if thepurchase-request confidence level is greater than or equal to apurchase-request threshold level, purchasing the target product orservice via the associated user-account; and otherwise, if thepurchase-request confidence level is less than the purchase-requestthreshold level, sending the speech segment to at least one guidecomputing system, the at least one guide system configured to receiveinput relating to the speech segment or the purchase request, provide asecond determination of the target product or service based on theinput, and purchase the target product or service via the associateduser-account.
 14. The non-transitory machine-readable storage medium ofclaim 13, wherein the operations further comprise: receiving an imagecomprising contextual details related to the purchase request, whereinthe first determination of the target product or service is furtherbased on the image.
 15. The non-transitory machine-readable storagemedium of claim 13, wherein the first determination of the targetproduct or service is further based on one or more predetermined userpreferences.
 16. The non-transitory machine-readable storage medium ofclaim 13, wherein the first determination of the target product orservice is further based on one or more previous purchases made via theassociated user-account.
 17. The non-transitory machine-readable storagemedium of claim 13, wherein the first determination of the targetproduct or service is further based on one or more discounts associatedwith the purchase request.
 18. The non-transitory machine-readablestorage medium of claim 13, wherein the at least one guide computingsystem is further configured to send a target-product-or-service-detailrequest to a client device requesting details on the target product orservice, and the input for the second determination of the targetproduct or service includes the details provided by client device. 19.The non-transitory machine-readable storage medium of claim 13, whereinthe operations further comprise sending a purchase-approval request. 20.The non-transitory machine-readable storage medium of claim 13, whereinthe operations further comprise sending a confirmation-of-purchasemessage.
 21. The non-transitory machine-readable storage medium of claim13, wherein the input for providing the second determination of thetarget product or service includes at least one of an image withcontextual details related to the purchase request, one or morepredetermined user preferences, one or more previous purchases made viathe associated user-account, or one or more discounts associated withthe purchase request.